Reliable optical communication systems use mechanisms for minimizing the effects of signal degradation occurring between associated transmitters and receivers. Signal degradation occurs due to a variety of factors and is exacerbated by the long-haul transmission distances and high optical channel counts required in many applications. Due to signal degradation, some transmitted data may be incorrectly interpreted at a receiver. If data is misinterpreted at a rate above that which is acceptable, the efficacy and viability of the system may be lost.
A variety of techniques for minimizing the effects of signal degradation have been investigated. Forward Error Correction (FEC) is one technique used to help compensate for signal degradation and provide “margin improvements” to the system. Margin improvements generally allow an increase in amplifier spacing and/or increase in system capacity. In a Wavelength Division Multiplexing (WDM) system, for example, margin improvements obtained through FEC techniques allow an increase in the bit rate of each WDM channel and/or a decrease in the spacing between WDM channels.
FEC typically involves insertion of a suitable error correction code into a transmitted data stream to facilitate detection and correction of data errors about which there is no previously known information. Error correction codes are generated in a FEC encoder for the data stream and are sent to a receiver including a FEC decoder. The FEC decoder recovers the error correction codes and uses them to correct any errors in the received data stream.
Of course, the efficacy of FEC techniques is impacted by the ability of the optical signal receiver to correctly detect transmitted data and error correction codes. Improvements in receiver signal detection thus translate to improved performance of FEC codes in providing correction of bit errors. A known receiver configuration includes a decision circuit for converting the received data signal into a binary electrical signal, e.g. including logic ones and zeros representative of the transmitted data. The decision circuit may, for example, include a comparator for comparing the received data signal with a predetermined voltage level (the decision threshold). If the voltage level of the received data signal is above the decision threshold at a particular sample time, the comparator may output a logic one. If, however, the voltage level of the received data signal is below the decision threshold, the comparator may output a logic zero. The decision circuit thus makes an initial decision (i.e., a hard decision) as to the data bit values of the received data stream. The FEC decoder detects and corrects errors in the data stream established by the hard decision circuit. Therefore, the setting of the decision threshold in the decision circuit is important in achieving optimal system bit error rate (BER).
One way to enhance FEC decoding capabilities is the use of soft decision receivers or detectors in combination with soft decision FEC decoders. According to such soft decision schemes, the soft decision detector includes multiple decision circuits with different decision thresholds (e.g., different threshold voltage levels). The multiple decision circuits produce multiple bit “soft” information, as compared to the single bit (i.e., a one or a zero) that is provided for hard decision detection. An n-bit soft decision scheme uses 2n−1 decision thresholds. Three decision thresholds are used in a 2-bit soft decision scheme, for example, and seven decision thresholds are used in a 3-bit soft decision scheme. The multiple bit soft information represents a confidence level in the received data and provides the FEC decoder with additional information, for example, whether the bit was very likely one, likely one, likely zero, or most likely zero. The extra information allows the use of more efficient soft decision FEC decoders, which allow operation in more noisy or more distorted channel conditions.
Optimization of decision thresholds is desirable in error correction systems. In order to achieve maximum error correction capability of soft decision FEC decoders, for example, the position (i.e., voltage) of decision thresholds may be optimized depending on factors such as the signal to noise ratio, bit error rate (BER), signal distortion, and other factors. Moreover, performance of an optical communication system experiences variations over time including signal power fluctuations, signal-to-noise ratio fluctuations, fluctuations in signal distortions due to polarization effects, and other fluctuations. Thus, decision thresholds should be adjusted in real time responsive to time varying parameters of an optical data channel.
Some existing hard decision receivers may simply minimize the amount of received errors (e.g., minimize BER) by adjusting the position of the single hard decision threshold. Such BER information may be readily available from the FEC decoder, which decodes and counts received errors. In soft decision receivers, however, the BER information alone is insufficient to adjust or optimize the multiple soft decision thresholds.